Structure Prediction for Gland Segmentation With Hand-Crafted and Deep Convolutional Features

Boosting Hand-Crafted Features for Curvilinear Structure Segmentation by Learning Context Filters

Feeding Hand-Crafted Features for Enhancing the Performance of Convolutional Neural Networks

Since the convolutional neural network (CNN) is believed to find right features for a given problem, the study of hand-crafted features is somewhat neglected these days. In this paper, we show that finding an appropriate feature for the given problem may be still important as they can enhance the performance of CNN-based algorithms. Specifically, we show that feeding an appropriate feature to t...

Person re-identification with fusion of hand-crafted and deep pose-based body region features

Person re-identification (re-ID) aims to accurately retrieve a person from a large-scale database of images captured across multiple cameras. Existing works learn deep representations using a large training subset of unique persons. However, identifying unseen persons is critical for a good re-ID algorithm. Moreover, the misalignment between person crops to detection errors or pose variations l...

Enhancing Neural Disfluency Detection with Hand-Crafted Features

In this paper, we apply a bidirectional Long Short-Term Memory with a Conditional Random Field to the task of disfluency detection. Long-range dependencies is one of the core problems for disfluency detection. Our model handles long-range dependencies by both using the Long Short-Term Memory and hand-crafted discrete features. Experiments show that utilizing the hand-crafted discrete features s...

Automatic Lung Cancer Detection and Diagnosis Using Hand Crafted and Deep Learning Features

This paper presents a lung nodule detection and classification system which utilizes a combination of hand crafted and deep learning features. Hand crafted features were obtained from modified methods of bag of frequencies, and taxonomic indices. We included a robust radius estimation algorithm that resulted in an average error of 1.29 pixels. Hand crafted features were obtained from 3D low dos...