Results 61 to 70 of about 141,410 (272)
Attention Correctness in Neural Image Captioning
, 2016 Attention mechanisms have recently been introduced in deep learning for various tasks in natural language processing and computer vision. But despite their popularity, the "correctness" of the implicitly-learned attention maps has only been assessed ...
Liu, Chenxi +3 more
core +1 more source
, 2020 Automated captioning of photos is a mission that incorporates the difficulties of photo analysis and text generation. One essential feature of captioning is the concept of attention: how to determine what to specify and in which sequence. In this study, we leverage the Object Relation using adversarial robust cut algorithm, that grows upon this method ...
Yarnell, Daniel, Wang, Xian
openaire +2 more sources
Advanced Functional Materials, EarlyView.Polymorph engineering in ErMnO3 enables low‐voltage, forming‐free threshold switching with tunable negative differential resistance. Conducting orthorhombic regions embedded in an insulating hexagonal matrix provide controlled Joule‐heating‐enhanced Poole–Frenkel transport. The hexagonal phase prevents excessive heating and breakdown.
Rong Wu +8 more
wiley +1 more source
BMC Veterinary Research, 2018 The original article [1] contains an error whereby the caption in Figure 8 is incorrect; the correct caption can be seen ahead alongside its respective image.
M. Kaiser +7 more
doaj +1 more source
Image Caption Generation Using Contextual Information Fusion With Bi-LSTM-s
IEEE Access, 2023 The image caption generation algorithm necessitates the expression of image content using accurate natural language. Given the existing encoder-decoder algorithm structure, the decoder solely generates words one by one in a front-to-back order and is ...
Huawei Zhang +3 more
doaj +1 more source
Image Captioning with Semantic Attention
, 2016 Automatically generating a natural language description of an image has attracted interests recently both because of its importance in practical applications and because it connects two major artificial intelligence fields: computer vision and natural ...
Fang, Chen +4 more
core +1 more source
Advanced Healthcare Materials, EarlyView.Coagulative granular hydrogels are composed of packed thrombin‐functionalized microgels that catalyze the conversion of fibrinogen into a secondary fibrin network, filling the interstitial voids. This bio‐inspired approach stabilizes the biomaterial to match the robustness of bulk hydrogels without compromising injectability, mimicking the initial ...
Zhipeng Deng +16 more
wiley +1 more source
Evaluating Text-to-Image Matching using Binary Image Selection (BISON)
, 2019 Providing systems the ability to relate linguistic and visual content is one of the hallmarks of computer vision. Tasks such as text-based image retrieval and image captioning were designed to test this ability but come with evaluation measures that have
Hu, Hexiang +2 more
core +1 more source
ACapMed: Automatic Captioning for Medical Imaging
Applied Sciences, 2022 Medical image captioning is a very challenging task that has been rarely addressed in the literature on natural image captioning. Some existing image captioning techniques exploit objects present in the image next to the visual features while generating descriptions. However, this is not possible for medical image captioning when one requires following
Djamila Romaissa Beddiar +3 more
openaire +3 more sources
Aqueous Two‐Phase Bioinks for Discrete Packing and Compartmentalization of 3D Bioprinted Cells
Advanced Healthcare Materials, EarlyView.Aqueous two‐phase systems (ATPS) enable the formation of biomimetic interfaces crucial for tissue engineering. However, clinical translation remains limited by the challenge of precisely controlling cellular compartmentalization. Here, we developed ATPS biomaterial inks for 3D bioprinting allowing tuneable droplet formation via NaCl modulation.
Martina Marcotulli +17 more
wiley +1 more source