스터디 일정 & 커리큘럼 & 발표자료

진행 중 : PART II

PART II

  • 2015년 11월 24일 ~
  • DeepCV는 발표자료가 링크가 따로 없다면, 스탠포드 강좌 - Convolutional Neural Networks for Visual Recognition의 자료를 사용함
회차 일시 내용 발표자 발표자료
1 11/24 (지각심리) 5. Perceiving Objects and Scenes 박성영 발표자료
(CVPy) 5. Multiple View Geometry (1) 한태규 발표자료
(CVMetrics) 4: Local Feature Design Concepts, Classification, and Learning (1) 김무성 발표자료
(DeepCV) Convolutional Neural Networks: architectures, convolution / pooling layers 박경원
(딥코딩) Tensorflow (1) - 설치 & 오버뷰 김무성 발표자료
2 12/8 (지각심리) 6. Visual Attention 송숙영 발표자료
(CVPy) 5. Multiple View Geometry (2) 한태규 발표자료
(DeepCV) Understanding and visualizing Convolutional Neural Networks (1) 김무성
(딥코딩) Tensorflow (2) - MNIST For ML Beginners 권준호 발표자료
3 12/22 (지각심리) 7. Taking Action 박성영 발표자료
(딥코딩) Tensorflow (3) - Deep MNIST for Experts 이재황 발표자료
4 1/5 (지각심리) 8. Perceiving Motion 안홍석
(DeepCV) Understanding and visualizing Convolutional Neural Networks (2) 김무성
(딥코딩) Tensorflow (4) - TensorFlow Mechanics 101 이재황
5 1/19 (지각심리) 9. Perceiving Color
(CVPy) 6. Clustering Images
(DeepCV) What makes ConvNets tick, Transfer Learning
(CVPy) 5. Multiple View Geometry (3) 한태규 발표자료
(CVMetrics) 4: Local Feature Design Concepts, Classification, and Learning (2) 김무성 발표자료
6 2/2 (지각심리) 10. Perceiving Depth and Size
(CVMetrics) 5. Taxonomy of Feature Description Attributes
(DeepCV) Squeezing out the last few percent, Training ConvNets in practice
(딥코딩) Tensorflow (5) - Convolutional Neural Networks
7 2/16 (CVPy) 7. Searching Images
(CVMetrics) 6: Interest Point Detector and Feature Descriptor Survey
(DeepCV) Beyond Image Classification: localization, detection, segmentation. - Recurrent Networks I: Image Captioning example
(딥코딩) Tensorflow (6) - Recurrent Neural Networks
8 3/15 (CVPy) 8. Classifying Image Content
(CVMetrics) 7: Ground Truth Data, Content, Metrics, and Analysis
(DeepCV) Working with Caffe: hands-on tutorial with Justin
9 3/29 (CVPy) 9. Image Segmentation
(DeepCV) Mystery talk, Tiny ImageNet student spotlights, Recurrent Networks II, Attention
(딥코딩) Tensorflow (6) - Vector Representations of Words

예정 : PART III

완료 : PART I

PART I

  • 2015년 7월 7일 ~ 2015년 11월 10일
  • DeepCV는 발표자료가 링크가 따로 없다면, 스탠포드 강좌 - Convolutional Neural Networks for Visual Recognition의 자료를 사용함
회차 일시 내용 발표자 발표자료
1 7/7 (지각심리)1.Introductin to Perception(1) 김덕태 발표자료
(CVPy)1.Basic Image Handling and Processing 송근창 발표자료
(DeepCV)Intro to Computer Vision 김무성 발표자료
2 7/21 (CVMetrics) : 1: Image Capture and Representation 김덕태 발표자료
(DeepCV) : Image classification, data-driven approach, k-nearest neighbor 이재황
3 8/4 (지각심리) 2. The Beginnings of Perception 박성영 발표자료
(CVPy) 2. Local Image Descriptors 김무성 발표자료
(지각심리) 1. Introductin to Perception (2) 김덕태 발표자료
4 8/18 (CVPy) 3. Image to Image Mappings 한태규 발표자료
(CVMetrics) 2. Image Pre-Processing (1) 김덕태 발표자료
(DeepCV) Linear classification: SVM/Softmax 최홍용
5 9/1 (지각심리) 3. Neural Processing and Perception 송숙영 발표자료
(CVMetrics) 2. Image Pre-Processing (2) 김덕태 발표자료
(DeepCV) Optimization, higher-level representations, image features 김무성
6 9/15 (DeepCV) Introduction to Neural Networks, backpropagation 김무성
7 10/13 (CVMetrics) 2. Image Pre-Processing (3) 김덕태 발표자료
8 10/27 (CVPy) 4. Camera Models and Augmented Reality 최홍용 발표자료
(CVMetrics) 3. Global and Regional Features (1) 한태규 발표자료
(DeepCV) Getting Neural Networks to work: cross-validation process, optimization, debugging 김무성
9 11/10 (지각심리) 4. Cortical Organization 박성영 발표자료
(CVMetrics) 3. Global and Regional Features (2) 한태규 발표자료
Written on December 30, 2015