OBJECT CLASSIFICATION USING FAST SUPERVISED HASHING FOR HIGH DIMENSIONAL DATA

ISBN-13: 9786206172918 / Angielski / Miękka / 72 str.

M.Aravind Kumar

Opis

This book summarizes The primary concern of supervised hashing is to convert the original features into short binary codes that can maintain label similarity in the Hamming space. Due to their strong generalization capabilities, non-linear hash functions have shown to be superior than linear ones. Kernel functions are frequently utilized in the literature to create non-linear hashing, which results in encouraging retrieval performance but long evaluation and training times. Here, we suggest using boosted decision trees, which are quick to train and assess and are hence more suited for hashing with high dimensional data. As part of continuous improvement, we first suggest sub-modular formulations for the hashing binary code inference issue as well as an effective block search technique based on Graph Cut for large-scale inference. Then, we train boosted decision trees to suit the binary codes in order to learn hash functions. Experiments show that in terms of retrieval precision and training duration, our suggested strategy greatly surpasses the majority of state-of-the-art methods.

O autorze

Dr. M. Aravind Kumar obtained B. Tech Degree in ECE, M Tech Degree in VLSI System Design from JNTUH, and Ph.D. from GITAM University, Visakhapatnam He is working at the WEST GODAVARI INSTITUTE OF SCIENCE AND ENGINEERING as a Principal. He has 15 years of teaching experience. He is a Life member of FIE, ISTE, TETE, SCIEI, UACEE, and IAENG.