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Moreover, with pedestrians sometimes hiding in front of the model when distracted by confrontations, and confrontations causing the model to “ignore” roadblocks, researchers found several ways to trick Tesla’s autopilot system. A bug in the Tesla model S’s automatic wiper and lane recognition ...
Definition 1 The Conditional Average Treatment Effect (CATE) for unit u is: . We can now define the Average Treatment Effect (ATE) and the Average Treatment effect on the Treated (ATT) as: Because the joint distribution \(P(x, t, y_0, y_1)\) is unknown, we can only estimate CATE...
Recall that small or even imperceptible perturbations can force an ASR system to output a malicious command that was predefined by an adversary at a 100% success rate as shown in Table 3. Geirhos et al. [66] explained this “Clever Hans” behavior in DNNs via the concept of shortcut ...
We address the issue of functionality-preservation in adversarial learning in contrast to domains such as computer vision, whereby a malformed input must suitably fool a system process as well as a human user such that the original functionality is maintained despite some modification; We summarise ...
3.1. Definition of Safety AI must ensure minimum safety regardless of its purpose. In a field where AI is applied, the actual input data may not exist in the dataset used for training. Additionally, AI suffers from multiple threats in real-world applications, such as adversarial attacks (adver...
Inherent filtering is accomplished by limiting the presented results to those contained within the category intersection set {𝑐𝑣∩𝑐𝑏}cv∩cb as seen in the operational definition of conversion rate (Equation (4)). This set is interpreted as representing the greatest likelihood for ...
We begin by introducing the L α -GAN system. Definition 3. Fix α ∈ A ⊆ R and let L α : { 0 , 1 } × [ 0 , 1 ] → [ 0 , ∞ ) be a loss function such that y ^ L α 1 , y ^ 2 is a continuous function that is either convex or concave in y ^ ∈ [ 0 ...
This indicates that it can be operated even in an embedded system with limited computing resources. Moreover, from the attention maps in LCA-GAN and Grad-CAM images of DEX for images de-occluded with LCA-GAN, LCA-GAN and DEX effectively extracted features for de-occlusion and age estimation...
Therefore, it does not change the definition of the loss function. 𝐺G learns to generate images that are indistinguishable from real ones by learning the distribution of real samples: ℒ𝐺=−𝔼𝑧∼𝑃(𝑧)[log𝐷𝑈(𝐺(𝑧))]LG=−Ez∼PzlogDUGz (11) The generator ...