Search Results - (( semantics representation learning algorithm ) OR ( java application optimisation algorithm ))

Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…The running system shows an OOP semantic knowledge representation by intelligent agents.…”
Get full text
Get full text
Get full text

A deep autoencoder-based representation for Arabic text categorization by El-Alami, Fatima-Zahra, El Mahdaouy, Abdelkader, El Alaoui, Said Ouatik, En-Nahnahi, Noureddine

“…It consisted of three stages: (1) Extracting from Arabic WordNet the most relevant concepts based on feature selection processes (2) Features learning via an unsupervised algorithm for text representation (3) Categorizing text using deep Autoencoder. …”
Get full text
Get full text
Get full text

Learning a deeply supervised multi-modal RGB-D embedding for semantic scene and object category recognition by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

“…This technique motivates bilateral transfer learning between the modalities by taking the outer product of each feature extractor output. …”
Get full text
Get full text
Get full text
Get full text

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
Get full text
Get full text
Get full text

Effective query structuring with ranking using named entity categories for XML retrieval by Roko, Abubakar

“…The method employs Semantic Tags Extraction (STSE) algorithm to extract semantic tags of an element and Element Enrichment (EERM) algorithm to enrich the elements. …”
Get full text
Get full text
Get full text

Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…Furthermore, although pre-trained LLMs can generate contextualised word representation vectors, they lack the flexibility to modify the semantic significance of these vectors outside of the LLM, necessitating fine-tuning for the modification of word vectors. …”
Get full text
Get full text

Visual codebook analysis in image understanding / Hoo Wai Lam by Hoo, Wai Lam

“…The second contribution of this thesis is to reduce human annotation effort in zeroshot learning algorithm, by proposing hierarchical class concept. …”
Get full text
Get full text

Coherent crowd analysis with visual attributes / Nurul Japar by Nurul , Japar

“…Specifically, a collectiveness analysis framework is designed to quantify and detect collectiveness from individual-level to scene level. The incremental learning in this framework notably analyzes semantic relations among individuals and infers topological relationship propagation via a manifold learning algorithm. …”
Get full text
Get full text
Get full text

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
Get full text
Get full text

APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN by SARI, YUNITA SARI

“…For the third contribution, we have applied the Self-Training algorithm which is one of the semi-supervised machines learning technique. …”
Get full text
Get full text

Small target detection of Unmanned Aerial Vehicles based on GDWNet in the digital economy by Zhang, Yan, Zhang, Jing, Mustaffa, Mas Rina

“…During the feature fusion stage, DySample is employed to generate content-aware offsets through learning. This approach effectively breaks the fixed interpolation rules of traditional upsampling methods, enabling more dynamic, flexible, and semantically rich upsampling of the input feature maps, thereby improving the quality of feature integration. …”
Get full text
Get full text
Get full text