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"deep tracking"(으)로 6개의 도서가 검색 되었습니다.
9781032598079

Visual Object Tracking using Deep Learning

 | CRC Press
118,030원  | 20250626  | 9781032598079
The text comprehensively discusses tracking architecture under stochastic and deterministic frameworks and presents experimental results under each framework with qualitative and quantitative analysis. It covers deep learning techniques for feature extraction, template matching, and training the networks in tracking algorithms.
9783039439515

Tracking the Deep Biosphere through Time

 | Mdpi AG
102,880원  | 20210129  | 9783039439515
Deep biosphere research is at the scientific frontier of bio- and geo-related sciences, yet it is largely underexplored. In terms of volume, deep subsurface settings represent some of the largest microbial habitats on the planet, and the combined biomass of the deep biosphere encompasses the largest living reservoir of carbon, excluding land plants. However, the paleo-record of the deep biosphere is still largely uncharted and neglected.
9789811662447

Visual Object Tracking from Correlation Filter to Deep Learning

 | Springer
257,230원  | 20221120  | 9789811662447
The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning.
9786200781529

Real Time Multi Object Detection and Tracking Using Deep Learning

Philip, Felix M., Alapatt, Bosco Paul, Jims, Anupama  | Noor Publishing
86,360원  | 20200804  | 9786200781529
The era of digitization has paved the way for the emergence of multimedia technologies. The multimedia applications use a large video database. Applications such as video surveillance, traffic monitoring and live streaming of events need continuous monitoring of the video. Thus the video surveillance system for tracking multiple target objects from videos is one of the important research works.
9786203194814

Convective Cell Tracking through Deep Learning based Computer Vision

 | KS OmniScriptum Publishing
90,030원  | 20201215  | 9786203194814
The present study developed an autonomous algorithm for the Convective cell Identification and TRAcking (CITRA) using DWR reflectivity images. The CITRA algorithm is implemented in Python using Deep learning technique of Neural Networks. Optical Character Recognition is used in the present study through "Tesseract" which is an unsupervised Neural Network module based on LSTM which analyses the input dimensional pixel array/image and outputs high-level strings.
9780471445340

Radiometric Tracking Techniques for Deep-Space Navigation Paperback

 | Wiley
0원  | 99991230  | 9780471445340
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