MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01853nam a22002657i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20250819205612.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250722s |||ao||fr|||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9789390684687 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
EG-GaU |
| Transcribing agency |
EG-GaU |
| Modifying agency |
EG-GaU |
| Description conventions |
rda |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Edition number |
23 |
| Classification number |
006.3 |
| Item number |
S.B.E |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Sikka, Bharat, |
| Relator term |
author. |
| 9 (RLIN) |
60457 |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Elements of deep learning for computer vision : |
| Remainder of title |
explore deep neural network architectures, PyTorch, object detection algorithms, and computer vision applications for Python coders / |
| Statement of responsibility, etc. |
Bharat Sikka. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st edition. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
New Delhi : |
| Name of producer, publisher, distributor, manufacturer |
PB Publications, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2021. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
208 pages : |
| Other physical details |
illustrations ; |
| Dimensions |
24 cm. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1. An Introduction to Deep Learning ‡ 2. Supervised Learning ‡ 3. Gradient Descent ‡ 4. OpenCV with Python ‡ 5. Python Imaging Library and Pillow ‡ 6. Introduction to Convolutional Neural Networks ‡ 7. GoogLeNet, VGGNet, and ResNet ‡ 8. Understanding Object Detection ‡ 9. Popular Algorithms for Object Detection ‡ 10. Faster R‑CNN with PyTorch and YoloV4 with Darknet ‡ 11. Comparing Algorithms and API Deployment with Flask ‡ 12. Applications in Real World.<br/> |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Provides a thorough conceptual and practical introduction to deep learning in computer vision. Covers PyTorch-based neural network implementation, OpenCV/Pillow image handling, major CNN architectures (GoogLeNet, VGG, ResNet), object detection models (Faster R‑CNN, YOLOv4), and deployment via APIs. Ideal for developers seeking applied knowledge. :contentReference[oaicite:1]{index=1}<br/> |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Neural networks$xProgramming. |
| 9 (RLIN) |
60458 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Deep learning. |
| 9 (RLIN) |
60437 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |