example.bib

@article{Reference1,
	Abstract = {We have developed an enhanced Littrow configuration extended cavity diode laser (ECDL) that can be tuned without changing the direction of the output beam. The output of a conventional Littrow ECDL is reflected from a plane mirror fixed parallel to the tuning diffraction grating. Using a free-space Michelson wavemeter to measure the laser wavelength, we can tune the laser over a range greater than 10 nm without any alteration of alignment.},
	Author = {C. J. Hawthorn and K. P. Weber and R. E. Scholten},
	Journal = {Review of Scientific Instruments},
	Month = {12},
	Number = {12},
	Numpages = {3},
	Pages = {4477--4479},
	Title = {Littrow Configuration Tunable External Cavity Diode Laser with Fixed Direction Output Beam},
	Volume = {72},
	Url = {http://link.aip.org/link/?RSI/72/4477/1},
	Year = {2001}}

@article{Reference3,
	Abstract = {Operating a laser diode in an extended cavity which provides frequency-selective feedback is a very effective method of reducing the laser's linewidth and improving its tunability. We have developed an extremely simple laser of this type, built from inexpensive commercial components with only a few minor modifications. A 780~nm laser built to this design has an output power of 80~mW, a linewidth of 350~kHz, and it has been continuously locked to a Doppler-free rubidium transition for several days.},
	Author = {A. S. Arnold and J. S. Wilson and M. G. Boshier and J. Smith},
	Journal = {Review of Scientific Instruments},
	Month = {3},
	Number = {3},
	Numpages = {4},
	Pages = {1236--1239},
	Title = {A Simple Extended-Cavity Diode Laser},
	Volume = {69},
	Url = {http://link.aip.org/link/?RSI/69/1236/1},
	Year = {1998}}

@article{Reference2,
	Abstract = {We present a review of the use of diode lasers in atomic physics with an extensive list of references. We discuss the relevant characteristics of diode lasers and explain how to purchase and use them. We also review the various techniques that have been used to control and narrow the spectral outputs of diode lasers. Finally we present a number of examples illustrating the use of diode lasers in atomic physics experiments. Review of Scientific Instruments is copyrighted by The American Institute of Physics.},
	Author = {Carl E. Wieman and Leo Hollberg},
	Journal = {Review of Scientific Instruments},
	Keywords = {Diode Laser},
	Month = {1},
	Number = {1},
	Numpages = {20},
	Pages = {1--20},
	Title = {Using Diode Lasers for Atomic Physics},
	Volume = {62},
	Url = {http://link.aip.org/link/?RSI/62/1/1},
	Year = {1991}}

@inproceedings{pauwels2013real,
  title={Real-time model-based rigid object pose estimation and tracking combining dense and sparse visual cues},
  author={Pauwels, Karl and Rubio, Leonardo and Diaz, Javier and Ros, Eduardo},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={2347--2354},
  year={2013}
}
@article{lecun1989generalization,
  title={Generalization and network design strategies},
  author={LeCun, Yann and others},
  journal={Connectionism in perspective},
  pages={143--155},
  year={1989},
  publisher={Citeseer}
}
@book{goodfellow2016deep,
  title={Deep learning},
  author={Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron and Bengio, Yoshua},
  volume={1},
  year={2016},
  publisher={MIT press Cambridge}
}
@article{haj2017classifications,
  title={Classifications of multispectral colorectal cancer tissues using convolution neural network},
  author={Haj-Hassan, Hawraa and Chaddad, Ahmad and Harkouss, Youssef and Desrosiers, Christian and Toews, Matthew and Tanougast, Camel},
  journal={Journal of pathology informatics},
  volume={8},
  year={2017},
  publisher={Wolters Kluwer--Medknow Publications}
}
@inproceedings{lockhart2014limitations,
  title={Limitations with activity recognition methodology \& data sets},
  author={Lockhart, Jeffrey W and Weiss, Gary M},
  booktitle={Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication},
  pages={747--756},
  year={2014},
  organization={ACM}
}
@article{nazir2017inter,
  title={Inter and intra class correlation analysis (IICCA) for human action recognition in realistic scenarios},
  author={Nazir, Saima and Yousaf, Muhammad Haroon and Velastin, Sergio A},
  year={2017},
  publisher={IET}
}
@article{diba2018spatio,
  title={Spatio-Temporal Channel Correlation Networks for Action Classification},
  author={Diba, Ali and Fayyaz, Mohsen and Sharma, Vivek and Arzani, M Mahdi and Yousefzadeh, Rahman and Gall, Juergen and Van Gool, Luc},
  journal={arXiv preprint arXiv:1806.07754},
  year={2018}
}
@article{liu2018attentive,
  title={Attentive Crowd Flow Machines},
  author={Liu, Lingbo and Zhang, Ruimao and Peng, Jiefeng and Li, Guanbin and Du, Bowen and Lin, Liang},
  journal={arXiv preprint arXiv:1809.00101},
  year={2018}
}
@inproceedings{schuldt2004recognizing,
  title={Recognizing human actions: a local SVM approach},
  author={Schuldt, Christian and Laptev, Ivan and Caputo, Barbara},
  booktitle={Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on},
  volume={3},
  pages={32--36},
  year={2004},
  organization={IEEE}
}
@inproceedings{krizhevsky2012imagenet,
  title={Imagenet classification with deep convolutional neural networks},
  author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
  booktitle={Advances in neural information processing systems},
  pages={1097--1105},
  year={2012}
}
@article{xu2015empirical,
  title={Empirical evaluation of rectified activations in convolutional network},
  author={Xu, Bing and Wang, Naiyan and Chen, Tianqi and Li, Mu},
  journal={arXiv preprint arXiv:1505.00853},
  year={2015}
}
@article{srivastava2014dropout,
  title={Dropout: a simple way to prevent neural networks from overfitting},
  author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
  journal={The Journal of Machine Learning Research},
  volume={15},
  number={1},
  pages={1929--1958},
  year={2014},
  publisher={JMLR. org}
}
@article{lin2013network,
  title={Network in network},
  author={Lin, Min and Chen, Qiang and Yan, Shuicheng},
  journal={arXiv preprint arXiv:1312.4400},
  year={2013}
}
@article{rumelhart1986learning,
  title={Learning representations by back-propagating errors},
  author={Rumelhart, David E and Hinton, Geoffrey E and Williams, Ronald J},
  journal={nature},
  volume={323},
  number={6088},
  pages={533},
  year={1986},
  publisher={Nature Publishing Group}
}
@article{tripathi2016context,
  title={Context matters: Refining object detection in video with recurrent neural networks},
  author={Tripathi, Subarna and Lipton, Zachary C and Belongie, Serge and Nguyen, Truong},
  journal={arXiv preprint arXiv:1607.04648},
  year={2016}
}
@article{elman1990finding,
  title={Finding structure in time},
  author={Elman, Jeffrey L},
  journal={Cognitive science},
  volume={14},
  number={2},
  pages={179--211},
  year={1990},
  publisher={Wiley Online Library}
}
@article{lipton2015critical,
  title={A critical review of recurrent neural networks for sequence learning},
  author={Lipton, Zachary C and Berkowitz, John and Elkan, Charles},
  journal={arXiv preprint arXiv:1506.00019},
  year={2015}
}
@article{hochreiter1997long,
  title={Long short-term memory},
  author={Hochreiter, Sepp and Schmidhuber, J{\"u}rgen},
  journal={Neural computation},
  volume={9},
  number={8},
  pages={1735--1780},
  year={1997},
  publisher={MIT Press}
}
@article{gers1999learning,
  title={Learning to forget: Continual prediction with LSTM},
  author={Gers, Felix A and Schmidhuber, J{\"u}rgen and Cummins, Fred},
  year={1999},
  publisher={IET}
}
@inproceedings{nair2010rectified,
  title={Rectified linear units improve restricted boltzmann machines},
  author={Nair, Vinod and Hinton, Geoffrey E},
  booktitle={Proceedings of the 27th international conference on machine learning (ICML-10)},
  pages={807--814},
  year={2010}
}
@article{ioffe2015batch,
  title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
  author={Ioffe, Sergey and Szegedy, Christian},
  journal={arXiv preprint arXiv:1502.03167},
  year={2015}
}
@incollection{lecun2012efficient,
  title={Efficient backprop},
  author={LeCun, Yann A and Bottou, L{\'e}on and Orr, Genevieve B and M{\"u}ller, Klaus-Robert},
  booktitle={Neural networks: Tricks of the trade},
  pages={9--48},
  year={2012},
  publisher={Springer}
}
@inproceedings{glorot2010understanding,
  title={Understanding the difficulty of training deep feedforward neural networks},
  author={Glorot, Xavier and Bengio, Yoshua},
  booktitle={Proceedings of the thirteenth international conference on artificial intelligence and statistics},
  pages={249--256},
  year={2010}
}
@article{lecun2015deep,
  title={Deep learning},
  author={LeCun, Yann and Bengio, Yoshua and Hinton, Geoffrey},
  journal={nature},
  volume={521},
  number={7553},
  pages={436},
  year={2015},
  publisher={Nature Publishing Group}
}
@inproceedings{laptev2004recognizing,
  title={Recognizing human actions: a local SVM approach},
  author={Laptev, Ivan and Caputo, Barbara and others},
  booktitle={null},
  pages={32--36},
  year={2004},
  organization={IEEE}
}
@inproceedings{laptev2004recognizing,
  title={Recognizing human actions: a local SVM approach},
  author={Laptev, Ivan and Caputo, Barbara and others},
  booktitle={null},
  pages={32--36},
  year={2004},
  organization={IEEE}
}
@article{moussa2015enhanced,
  title={An enhanced method for human action recognition},
  author={Moussa, Mona M and Hamayed, Elsayed and Fayek, Magda B and El Nemr, Heba A},
  journal={Journal of advanced research},
  volume={6},
  number={2},
  pages={163--169},
  year={2015},
  publisher={Elsevier}
}
@article{bregonzio2012fusing,
  title={Fusing appearance and distribution information of interest points for action recognition},
  author={Bregonzio, Matteo and Xiang, Tao and Gong, Shaogang},
  journal={Pattern Recognition},
  volume={45},
  number={3},
  pages={1220--1234},
  year={2012},
  publisher={Elsevier}
}
@inproceedings{liu2008learning,
  title={Learning human actions via information maximization},
  author={Liu, Jingen and Shah, Mubarak},
  booktitle={2008 IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1--8},
  year={2008},
  organization={IEEE}
}
@inproceedings{lin2009recognizing,
  title={Recognizing actions by shape-motion prototype trees},
  author={Lin, Zhe and Jiang, Zhuolin and Davis, Larry S},
  booktitle={2009 IEEE 12th international conference on computer vision},
  pages={444--451},
  year={2009},
  organization={IEEE}
}
@article{chen2009mosift,
  title={Mosift: Recognizing human actions in surveillance videos},
  author={Chen, Ming-yu and Hauptmann, Alexander},
  year={2009},
  publisher={Citeseer}
}
@article{niebles2008unsupervised,
  title={Unsupervised learning of human action categories using spatial-temporal words},
  author={Niebles, Juan Carlos and Wang, Hongcheng and Fei-Fei, Li},
  journal={International journal of computer vision},
  volume={79},
  number={3},
  pages={299--318},
  year={2008},
  publisher={Springer}
}
@inproceedings{tran2011modeling,
  title={Modeling motion of body parts for action recognition.},
  author={Tran, Khai N and Kakadiaris, Ioannis A and Shah, Shishir K},
  booktitle={BMVC},
  volume={11},
  pages={1--12},
  year={2011},
  organization={Citeseer}
}
@inproceedings{fathi2008action,
  title={Action recognition by learning mid-level motion features},
  author={Fathi, Alireza and Mori, Greg},
  booktitle={2008 IEEE Conference on Computer Vision and Pattern Recognition},
  pages={1--8},
  year={2008},
  organization={IEEE}
}
@inproceedings{kovashka2010learning,
  title={Learning a hierarchy of discriminative space-time neighborhood features for human action recognition},
  author={Kovashka, Adriana and Grauman, Kristen},
  booktitle={2010 IEEE computer society conference on computer vision and pattern recognition},
  pages={2046--2053},
  year={2010},
  organization={IEEE}
}
@inproceedings{cao2010cross,
  title={Cross-dataset action detection},
  author={Cao, Liangliang and Liu, Zicheng and Huang, Thomas S},
  booktitle={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  pages={1998--2005},
  year={2010},
  organization={IEEE}
}
@inproceedings{kaaniche2010gesture,
  title={Gesture recognition by learning local motion signatures},
  author={Ka{\^a}niche, Mohamed B{\^e}cha and Bremond, Fran{\c{c}}ois},
  booktitle={2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  pages={2745--2752},
  year={2010},
  organization={IEEE}
}
@inproceedings{dollar2005behavior,
  title={Behavior recognition via sparse spatio-temporal features},
  author={Doll{\'a}r, Piotr and Rabaud, Vincent and Cottrell, Garrison and Belongie, Serge},
  year={2005},
  organization={VS-PETS Beijing, China}
}
@inproceedings{klaser2008spatio,
  title={A spatio-temporal descriptor based on 3d-gradients},
  author={Klaser, Alexander and Marsza{\l}ek, Marcin and Schmid, Cordelia},
  booktitle={BMVC 2008-19th British Machine Vision Conference},
  pages={275--1},
  year={2008},
  organization={British Machine Vision Association}
}
@inproceedings{klaser2008spatio,
  title={A spatio-temporal descriptor based on 3d-gradients},
  author={Klaser, Alexander and Marsza{\l}ek, Marcin and Schmid, Cordelia},
  booktitle={BMVC 2008-19th British Machine Vision Conference},
  pages={275--1},
  year={2008},
  organization={British Machine Vision Association}
}
@article{rodriguez2010spatio,
  title={Spatio-temporal maximum average correlation height templates in action recognition and video summarization},
  author={Rodriguez, Mikel},
  year={2010},
  publisher={Citeseer}
}
@inproceedings{ke2005efficient,
  title={Efficient Visual Event Detection Using Volumetric Features.},
  author={Ke, Yan and Sukthankar, Rahul and Hebert, Martial and others},
  booktitle={ICCV},
  volume={1},
  number={1},
  pages={166--173},
  year={2005},
  organization={Citeseer}
}
@inproceedings{laptev2008learning,
  title={Learning realistic human actions from movies},
  author={Laptev, Ivan and Marsza{\l}ek, Marcin and Schmid, Cordelia and Rozenfeld, Benjamin},
  booktitle={CVPR 2008-IEEE Conference on Computer Vision \& Pattern Recognition},
  pages={1--8},
  year={2008},
  organization={IEEE Computer Society}
}
@inproceedings{wang2011action,
  title={Action recognition by dense trajectories},
  author={Wang, Heng and Kl{\"a}ser, Alexander and Schmid, Cordelia and Cheng-Lin, Liu},
  booktitle={CVPR 2011-IEEE Conference on Computer Vision \& Pattern Recognition},
  pages={3169--3176},
  year={2011},
  organization={IEEE}
}
@inproceedings{wang2012comparative,
  title={A comparative study of encoding, pooling and normalization methods for action recognition},
  author={Wang, Xingxing and Wang, LiMin and Qiao, Yu},
  booktitle={Asian Conference on Computer Vision},
  pages={572--585},
  year={2012},
  organization={Springer}
}
@inproceedings{grushin2013robust,
  title={Robust human action recognition via long short-term memory},
  author={Grushin, Alexander and Monner, Derek D and Reggia, James A and Mishra, Ajay},
  booktitle={The 2013 International Joint Conference on Neural Networks (IJCNN)},
  pages={1--8},
  year={2013},
  organization={IEEE}
}
@inproceedings{veeriah2015differential,
  title={Differential recurrent neural networks for action recognition},
  author={Veeriah, Vivek and Zhuang, Naifan and Qi, Guo-Jun},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={4041--4049},
  year={2015}
}
@article{zhen2016action,
  title={Action recognition via spatio-temporal local features: A comprehensive study},
  author={Zhen, Xiantong and Shao, Ling},
  journal={Image and Vision Computing},
  volume={50},
  pages={1--13},
  year={2016},
  publisher={Elsevier}
}
@article{shi2017sequential,
  title={Sequential deep trajectory descriptor for action recognition with three-stream CNN},
  author={Shi, Yemin and Tian, Yonghong and Wang, Yaowei and Huang, Tiejun},
  journal={IEEE Transactions on Multimedia},
  volume={19},
  number={7},
  pages={1510--1520},
  year={2017},
  publisher={IEEE}
}