For the object detection network, we have used Faster RCNN. 

Implementation :  https://github.com/tryolabs/luminoth/tree/master/luminoth (Tensorflow Implementation)

We have used Resnet-101 as the base network to extract CNN- features. For that, we utilized the pre-trained weight and fine-tuned the network after block 2. 

Optimizer : SGD with momentum 0.9, learning rate 0.0003

Anchors:  base_size: 256 ,scales: [0.25, 0.5] , ratios: [1, 2]

Best result so far.

Limited the maximum class detection to 17 and changed the optimizer to Adam. Didn't perform well.

Average Precision (AP) @ [0.50] = 0.920

Average Precision (AP) @ [0.75] = 0.566

Average Precision (AP) @ [0.50:0.95] = 0.526

Average Recall (AR) @ [0.50:0.95] = 0.603

Removed the maximum class detection and kept the optimizer as Adam, still poor performance.

Average Precision (AP) @ [0.50] = 0.961

Average Precision (AP) @ [0.75] = 0.588

Average Precision (AP) @ [0.50:0.95] = 0.552

Average Recall (AR) @ [0.50:0.95] = 0.637