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From the Editor

Dedicated to Data Science, Machine Learning, and Applied Intelligence, we recently published a series exploring some of the most important developments in Photo Intelligence — including the growing challenge of image authenticity. Let’s face it: we’ve lost the ability to fully trust what we see. Real images are edited, filtered, enhanced, and computationally processed, while AI-generated or AI-enhanced images are no longer obviously fake. As a result, synthetic media analysis increasingly requires a new form of Visual Forensics: technical image analysis that sheds light on often conflicting signals of manipulation, editing, diffusion, provenance, and authenticity. Not just detection — but reasoning and explanation aimed at deeper understanding. We kick off with a post explaining in depth, why AI Image Detection is broken. The next post takes the conceptual shift from uncovering to reasoning. We go Beyond AI Detection in Building SignalLens, probing the processes that contributed to an image becoming what it currently is.

 

Editor's Pick

Visual Forensics

Beyond AI Detection: Building SignalLens

Figure 1: The Detector Problem Toward Explainable Visual Forensics A previous article exposed what I called the collapse of visual certainty. In short, it’s getting increasingly...
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Photo Intelligence

Visual Forensics

Models

LSTM Sequence Length Helper

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Helpers for LSTM models For predicting time series, such as the daily or hourly price history of financial assets like cryptocurrencies or stock tickers, LSTM...
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ARIMA – SARIMAX Models: Using the Model for Price Prediction

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Price Forecasting using Current Data with a Pre-Trained Mode Using the model for price prediction. Armed with a well trained model optimized for trading and...
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Avoiding Timeseries Generator ‘Version Hell’

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A Custom Sequence Generator for Keras The need for a custom sequence generator for Keras arises because the world of AI is constantly evolving. Vendors...
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ARIMA – SARIMAX models: Optimizing for Training

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ARIMA Family Time series forecasting with ARIMA - SARIMAX. These models provide powerful tools for predicting future price values based on historical data patterns. Among...
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Data

Synchronizing Data Frames from Different Time Zones

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Synchronizing data frames from different time zones is a requirement to be able to work consistently with a uniform time indication especially with (price)...
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LSTM Sequence Length Helper

Data coder -
Helpers for LSTM models For predicting time series, such as the daily or hourly price history of financial assets like cryptocurrencies or stock tickers, LSTM...
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Feature Engineering

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Feature engineering is the process of transforming raw data into relevant information for use by machine learning models. In other words, feature engineering is the process...
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Technical Analysis

Coding

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