arXiv:1602.07125
Car Type Recognition with Deep Neural Networks
원문 초록
In this paper we study automatic recognition of cars of four types: Bus, Truck, Van and Small car. For this problem we consider two data driven frameworks: a deep neural network and a support vector machine using SIFT features. The accuracy of the methods is validated with a database of over 6500 images, and the resulting prediction accuracy is over 97 %. This clearly exceeds the accuracies of earlier studies that use manually engineered feature extraction pipelines.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
CoDi: Co-evolving Contrastive Diffusion Models for Mixed-type Tabular Synthesis
Revisiting Deep Learning for Variable Type Recovery
Mask Detection and Classification in Thermal Face Images
TypeT5: Seq2seq Type Inference using Static Analysis
Safe-DS: A Domain Specific Language to Make Data Science Safe
Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text
토론
이 논문과 연결된 포럼 글이 아직 없습니다.