An Efficient Technique for Image Captioning using Deep Neural Network
원문 초록
With the huge expansion of internet and trillions of gigabytes of data generated every single day, the needs for the development of various tools has become mandatory in order to maintain system adaptability to rapid changes. One of these tools is known as Image Captioning. Every entity in internet must be properly identified and managed and therefore in the case of image data, automatic captioning for identification is required. Similarly, content generation for missing labels, image classification and artificial languages all requires the process of Image Captioning. This paper discusses an efficient and unique way to perform automatic image captioning on individual image and discusses strategies to improve its performances and functionalities.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
When VLMs Meet Image Classification: Test Sets Renovation via Missing Label Identification
Hashed Watermark as a Filter: Defeating Forging and Overwriting Attacks in Weight-based Neural Network Watermarking
ViT-ProtoNet for Few-Shot Image Classification: A Multi-Benchmark Evaluation
MVNet: Hyperspectral Remote Sensing Image Classification Based on Hybrid Mamba-Transformer Vision Backbone Architecture
Beyond Accuracy: Metrics that Uncover What Makes a 'Good' Visual Descriptor
토론
이 논문과 연결된 포럼 글이 아직 없습니다.