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Related Concept Videos

Language01:16

Language

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Language is a unique communication system that uses words and systematic rules to organize and transmit information. Unlike other forms of communication, which may involve postures, movements, odors, or vocalizations, language relies on symbols and grammar. This makes human communication distinct from that of other species, who also communicate but do not use language in the same way humans do.
Corballis and Suddendorf (2007) and Tomasello and Rakoczy (2003) highlight the role of language in...
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Components of Language01:24

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Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
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Language Development01:22

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Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
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Language and Cognition01:27

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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
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Understanding how an object moves along a path requires distinguishing between motion over a time span and motion at a precise moment. A useful example is a vehicle traveling along a straight and level path, where its position at any given time is known. The initial step in analyzing this motion is to measure how far the vehicle travels over a fixed time period. This measurement, called average velocity, is computed by dividing the total change in position by the duration over which the change...
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Related Experiment Video

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Novel Object Recognition Test for the Investigation of Learning and Memory in Mice
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Object-guided contrastive language-image pre-training for zero-shot target recognition.

Chenghao Zheng1

  • 1Southwest China Institute of Electronic Technology, Chengdu, 610036, Sichuan, China. zch.512@163.com.

Scientific Reports
|January 28, 2026
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Summary

Object-Guide CLIP (OG-CLIP) enhances visual-language models for security by improving target recognition. It achieves higher accuracy through knowledge graphs, region-focused processing, and adaptive features, outperforming standard models.

Keywords:
Attention mechanismComputer visionDeep learningObject recognition

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Traditional Visual-Language Models (VLMs) face limitations in semantic data, background suppression, and multi-resolution feature handling for security applications.
  • CLIP, a prominent VLM, exhibits constraints in recognizing diverse targets due to insufficient training data semantics and rigid feature processing.

Purpose of the Study:

  • To introduce Object-Guide CLIP (OG-CLIP), an advanced VLM designed for superior target recognition in security systems.
  • To overcome the limitations of existing VLMs by integrating novel data augmentation, target-centric processing, and adaptive feature representation.

Main Methods:

  • Knowledge graph-driven data augmentation using a 5000-category military knowledge graph and one million image-text pairs.
  • A target-centered Region of Interest (ROI) module that fuses SAM 2 masks with ViT features for enhanced focus and background suppression.
  • Adaptive Multi-Resolution Learning (MRL) with continuous features and dynamic dimension weighting for flexible granularity.

Main Results:

  • OG-CLIP achieved 84.28% mean Accuracy (mAcc) across 99 target categories, surpassing baseline CLIP by 11.36 percentage points.
  • Ablation studies confirmed the significant contribution of each proposed component to the overall performance.
  • The model demonstrated superior performance in complex scenarios, highlighting its robustness.

Conclusions:

  • OG-CLIP presents a scalable and adaptable vision-language modeling framework for military target recognition.
  • The proposed enhancements effectively address semantic limitations, background noise, and feature inflexibility in traditional VLMs.
  • Future research directions include expanding the dataset and optimizing the model for efficiency.