Israel Machine Vision Conference (IMVC 2024) April 8, 2024 abstract

"Deep Learning for ALL: Enhancing Image Inputs - Building Knowledge Outputs"

Building Image Intelligence

enhancing image inputs - unlocking hidden data

Maximizing the Value of Image Assets

Patents: 10,582,189 || 11,328,822 || 11,298,062 || 11,158,060 || 11,176,675 || 11,347,831 || WO2020121302 || 17/890,289

Mission

conflu3nce's mission is to transform early detection and predictive capabilities, applying its patented and patent-pending image-based solutions to: 1) Address health disparity and bias issues; 2) Personalize healthcare solutions; and, 3) Improve health outcomes for vulnerable and at-risk populations, and by default for ALL people.

Image-Based Technologies

From early disease detection to searching the proverbial "needle in the haystack" to developing personalized stimuli to support cognitive health, conflu3nce's tools integrate a top-down and bottom-up approach to build image intelligence and improve ROI visualization, anomaly detection, and overall image and scene analysis for both humans and machines.

The cornerstone of the company's product development initiative is the patented Stitch n' Peel (SnP) method. SnP logically juxtaposes non-contiguous image sections to identify long-term dependencies within an image. The approach enhances visual attention, reduces pixel volume, and deconstructs image complexity - - a technology Gestalt that balances ambiguity and clarity to help bridge the gap between human cognition, perception and computer vision.

SnP leverages an image's contiguity attributes; its embedded visual cues. These attributes can be algorithmically analyzed, and symmetries and differences across the image identified. The integration of these Estalt based visual cues can then be used to anchor local and global spatial and contextual relationships between parts of an image and help improve scene understanding.

SnP technology can be used to: 1) identify salient features; 2) optimize image search; 3) refine lesion analysis with edge-to-edge analyses; or, 4) enhance self-attention of long-range dependencies across complex image scenes for both humans and machines.

As a Vision Transformer, Stitch-ViT combines positional encoding with contiguity-based spatial awareness in computer vision - a process similar to how embedded Gestalt visual cues informs our perception and cognition of visual scenes and allowing us to assess, anticipate, infer, and predict local and global (near and far) interactions with the world around us.

SnP can be combined with ViZEZE to disambiguate and enhance an image's visual features, and SCORES - a Serial Color Reduction Segmentation method that facilitates a comparison between and within interior to edge to background characteristics, conflu3nce's technologies can be applied across diverse industries to build image intelligence by enhancing inputs.

Learn More
PICSSi - Personalizing Cognitive || LesionOptix - Medical Image Processing & Analysis || ImageOptix - Non-Medical Image Processing

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