IAST-CAC-UNet-LLCNN-BreastCancerCNN-ImageRetrieval_DF_CDVS-Highly_Efficient_Follicular_Segmentation

This repo. provides a list of implementations (including codes or dataset) for our previous papers. Most of the implementations were forked form the members of our group. However, the maintenance of the implementations will be based on the following list:

1. IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)

2. CAC-UNet: Multi-level-colonoscopy-malignant-tissue-detection-with-adversarial-CAC-UNet (Neurocomputing 2021)

3. LLCNN: A convolutional neural network for low-light image enhancement (VCIP 2017)

4. BreastCancerCNN: Breast cancer histopathology image classification through assembling multiple compact CNNs (BMC 2019)

5. ImageRetrieval_DF_CDVS: Feature Fusion for Image Retrieval with Adaptive Bitrate Allocation and Hard Negative Mining

6. Hybrid Model Enabling Highly Efficient Follicular Segmentation (Intelligent Medicine 2021)

7. Breast Cancer Image Classification On WSI With Spatial Correlations (ICASSP 2019)

8. A Channel-level Pruning Strategy for Convolutional Neural Networks